AC miro-mcp
Connect OpenClaw agents to Miro via Model Context Protocol (MCP). Use when generating diagrams, visualizing code, brainstorming board layouts, or integrating Miro into AI-powered design workflows. Supports OAuth 2.1 authentication, 14+ MCP-compatible clients (Cursor, Claude Code, Replit, Lovable, VSCode/Copilot, Gemini CLI, Windsurf, Kiro CLI, Amazon Q, others). Best for design thinking, architecture visualization, project planning, collaborative ideation.
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 2
✓ No critical or high findings
Medium and low: 2
-
low Obfuscation
obf-base64-blobreferences/rest-api-essentials.md:489Long base64-looking blob (quoted — discussed, not commanded)"data": "iVBO…mNk+M9QD…ggg==",
quoted -
low Exfiltration
net-credential-useSKILL.md:179Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)curl -H "Authorization: Bearer $ACCESS_TOKEN" https://api.miro.com/v2/...
vendor-host
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 51/100
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 6 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 50 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3032 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +3Description length 460: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 50 items
- +4Has examples (11 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.